Importing users from an Excel or OpenDocument workbook

You can upload a spreadsheet directly — there is no need to convert it to CSV first. The importer accepts Excel (.xlsx), OpenDocument (.ods) and CSV (.csv). A Google Sheet has to be downloaded in one of those formats before uploading.

Starting the import

Open the base group you want to import into and go to its Users tab.
Select Import. The dialog offers a direct upload, a Download Sample CSV link, and the Import Wizard.
Choose Import Wizard.

the Import dialog on a group's Users tab, offering Download Sample CSV and Import Wiz

Import is only possible into a base group. System groups and dynamic recipient groups are filled automatically and cannot be imported into.

The five steps of the wizard

Step	What you do
1 Upload	Select the workbook or CSV file
2 Sheet	Choose which sheet of the workbook to import
3 Configure	Set the header option, decide how existing users are treated, and map the columns
4 Data Cleansing	Choose which flawed rows are rejected
5 Import	Run the import and collect the result

Import Wizard on step 1, showing all five steps

Step 2 — Sheet

A workbook can hold several sheets, so the wizard asks which one carries the users. A CSV file has only one, and the step passes straight through.

Import Wizard on step 2, choosing the sheet of the workbook

Step 3 — Configure

This is where most import problems are avoided:

First row contains headers — whether the first row holds column names rather than data.
Existing users — Update existing overwrites the records of users already in

the system; Skip existing leaves them untouched and imports only new ones.

Field mapping — for every column of your file, pick the Cyberdise field it feeds,

or Skip this column for the ones you do not want to import.

Refresh preview — redraws the preview table underneath with your current settings.

Read the preview before moving on. It shows your real data as the importer will interpret it, which is the fastest way to catch a mapping mistake.

Import Wizard on step 3 with the header option, the Update/Skip choice, the field mapping

Step 4 — Data Cleansing

Rows that are incomplete or repeated are filtered here. The checks are applied in a fixed order, and the first one that rejects a row wins:

#	Check	Behaviour
1	Partial duplicates	Rejected
2	Full duplicates	The first row is kept, the repeats are rejected
3	E-mail and phone missing	Rejected
4	Incorrect e-mail format	Rejected
5	Incorrect phone format	Rejected
6	E-mail missing	Optional
7	Phone missing	Optional
8	Another field missing	Optional

Step 5 — Import

The final step shows the running status, the total number of rejected rows and a breakdown by rejection reason. When the import finishes you can download a feedback workbook: your original file with three sheets added.

Added sheet	Contents
`Import - <timestamp> - success`	The rows that were imported
`Import - <timestamp> - full duplicates`	Rows dropped as repeated duplicates
`Import - <timestamp> - fail`	Rows that failed for any other reason

Fix the rejected rows in that workbook and upload it again. Your last import and cleansing configuration is reused for the next upload, and you can override it.

Troubleshooting

Almost every row is reported as "Full duplicate", plus one "e-mail and phone missing". This is the signature of a broken field mapping, not of duplicate data. When no column is mapped to e-mail or phone, every row is read as empty, so all rows look identical to one another — the first is kept and the rest are counted as full duplicates. Go back to Configure, check First row contains headers, confirm that the e-mail column is mapped, and use Refresh preview to see real values before continuing.

The wrong columns appear in the preview. Check First row contains headers — with the setting inverted, the header row is read as data and the whole mapping shifts by one row.

CSV Import — the

CSV file structure, custom variables and the *Delete Users Not in CSV* option.